Results 121 to 130 of about 72,454 (299)
Engineered Metal–Organic Frameworks‐Based Materials for Environmental Detection
ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.Engineered metal–organic frameworks (MOFs) regulated by various material modification strategies are discussed for environmental contaminant detection under different sensing mechanisms, providing future improvements of MOFs in environmental detection. Sensitive and selective detection of contaminants is crucial for environmental protection.
Pan Gao +3 more
wiley +1 more source
The relationship between inflation, output growth, and their uncertainties: Nonlinear Multivariate GARCH-M evidence [PDF]
In this paper, we propose a nonlinear multivariate GARCH-M model. We have illustrated the actual modelling by applying the models to inflation and output growth variables and found that the effects of real and nominal uncertainties are regime-dependent ...
Tolga Omay
core
GARCH CLASS MODELS PERFORMANCE IN CONTEXT OF HIGH MARKET VOLATILITY [PDF]
, 2014 In the presented paper GARCH class models were considered for describing and forecasting market volatility in context of the economic crisis. The sample composition was designed to emphasize models performance in two groups of markets: well-developed and
Małecka, Marta
core +1 more source
Hydride Nitrides: Crystal Structure Redetermination of LiSr2H2N and the Isostructural LiBa2H2N
European Journal of Inorganic Chemistry, EarlyView.The quaternary hydride nitrides LiSr2H2N and LiBa2H2N are obtained in a non‐centrosymmetric crystal structure, different from previous reports. Crystal growth of the honey‐ and pale‐yellow compounds and essentially single phase synthesis is successful using alkali metal flux. The resulting fully ordered structures do not account for a structural reason
Chen Liang, Rainer Niewa
wiley +1 more source
Long memory with Markov-Switching GARCH [PDF]
The paper considers the Markov-Switching GARCH(1,1)-model with time-varying transition probabilities. It derives su?cient conditions for the square of the process to display long memory and provides some additional intuition for the empirical observation
Krämer, Walter
core +3 more sources
Journal of Forecasting, EarlyView.ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann +2 more
wiley +1 more source
Estimation of temporally aggregated multivariate GARCH models [PDF]
This paper investigates the performance of quasi maximum likelihood (QML) and nonlinear least squares (NLS) estimation applied to temporally aggregated GARCH models.Since these are known to be only weak GARCH, the conditional variance of the aggregated ...
Hafner, C.M., Rombouts, J.V.K.
core +1 more source
Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices
Journal of Forecasting, EarlyView.ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer +3 more
wiley +1 more source
Evaluation of Hedge Fund Returns Value at Risk Using GARCH Models [PDF]
The aim of this research paper is to evaluate hedge fund returns Value-at-Risk by using GARCH models. To perform the empirical analysis, one uses the HFRX daily performance hedge fund strategy subindexes and spans the period March 2003 – March 2008.
Sabrina Khanniche
core
A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios
Journal of Forecasting, EarlyView.ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley +1 more source